Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Lead product strategy for GenAI safety across Pinterest: build proactive safety frameworks, run threat modeling and red-teaming, translate policy into product requirements, define safety metrics, manage incident response, and collaborate cross-functionally to ensure equitable, scalable AI safeguards.

Design, build, and maintain backend services for contract lifecycle and billing (CPA and CPM models). Develop APIs, ensure auditability and data integrity, improve observability and reliability, partner with Product/Finance/Data, own services and data models, lead technical design, and mentor engineers.

Lead AI/ML-driven merchant and shopping product strategy, define vision, partner with Engineering, Data Science, Design and Marketing, launch personalization and LLM-powered experiences, set metrics, prioritize opportunities, and guide cross-functional teams to deliver scalable merchant discovery and shopping features.

Lead design and implementation of large-scale recommendation and decisioning systems for advertiser and seller workflows. Build unified context layers and agent foundations, own end-to-end ML lifecycle from problem framing to deployment, develop evaluation and feedback loops, apply retrieval/ranking/embeddings and agentic AI techniques, and mentor engineers while driving multi-quarter ML roadmaps.

Lead complex, cross-functional platform and infrastructure programs using AI-first approaches. Drive roadmaps, dependency and risk management, dashboards and reporting, prototype AI-assisted tools, ensure AI safety and governance, and coordinate stakeholders to improve developer productivity, reliability, and scalability across Ads and Core Infrastructure.

Lead cross-functional Monetization Data Science programs to build a trusted SSOT, instrumentation, production data pipelines, and self-serve analytics. Drive automation, monitoring, governance, and input-metrics cadences, run deep-dive analyses, and embed AI-first workflows and safety-by-design for scalable decision-making and reduced operational toil.

Design, analyze, and scale experimentation systems: research methodologies, improve experiment setup and evaluation, build workflows to expose experiment metadata, and consult with product teams to debug and optimize experiments.

Lead the Content and User Understanding ML organization, set multi-year ML/AI vision and technical strategy, drive VLM/LLM and large-scale deep learning innovation, ensure scalable deployment across product surfaces, partner with product and engineering for business impact, and hire and develop managers and engineers.

Apply quantitative modeling, experimentation, and ML to product and business problems. Build analysis pipelines, prototype models, instrument experiments, manipulate large web-scale datasets, and communicate insights to cross-functional partners to improve Pinterest products for millions of users.

Lead data science work for a CTV/adtech platform: write production Python code, design and analyze experiments, build reporting and analytics tools, translate insights into product, and collaborate with stakeholders to optimize ad campaigns.